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Building a citator through indirect crowdsourcing: Fastcase’s Bad Law Bot

Fastcase announced today the impending release of a new algorithm enhancement to their Authority Check system—dubbed Bad Law Bot (BLB)—whose job is to identify other opinions that indicate the case you found has been treated negatively. I won’t go into the particulars (go see Greg Lambert’s post over at 3 Geeks this morning) other than to say that if you practice in a jurisdiction that requires citation to subsequent appellate history (sigh, like Texas) and you frequently use other cases (regardless of relevancy to your issue) to tell you that information, then you’ll understand exactly what BLB does.

Fastcase BLB

I don’t know from “Big Data,” but BLB basically does what many attorneys do manually, it just reduces the friction of getting there, and for that it should be applauded. Although relying on the work of other attorneys can be a tricky business, if the information is there, why not push it a little closer to the top and let the user determine its value? Loislaw, for example, attempts to merge appellate court docket data with opinions to expose subsequent appellate treatment, but I think BLB’s approach probably would be better: find citing cases, pull the data from the cites, and display it for the user. (HINT.) Now imagine how much better BLB could be if were allowed to see the entire network of briefs, where much more case and statutory law is cited. Magnitudes.

Beyond the launch of BLB, I give Fastcase a +1 for being very clear to users about the algorithm’s limitations. They aren’t trying to pull one over on you; they’re just letting you know there’s this cool new tool that will save you some time, but like anything there are always limitations. Check out BLB’s page here.

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